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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationWed, 28 Oct 2009 13:00:08 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/28/t12567567314bz0ygfnf2hg099.htm/, Retrieved Sun, 05 May 2024 22:51:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51742, Retrieved Sun, 05 May 2024 22:51:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Kernel Density Estimation] [eigen graf] [2009-10-28 19:00:08] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
- RMPD      [Pearson Correlation] [] [2009-11-02 10:22:36] [ba905ddf7cdf9ecb063c35348c4dab2e]
- RM          [Kendall tau Rank Correlation] [] [2009-11-02 10:24:42] [ba905ddf7cdf9ecb063c35348c4dab2e]
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Dataseries X:
100.80
101.33
101.88
101.85
102.04
102.22
102.63
102.65
102.54
102.37
102.68
102.76
102.82
103.31
103.23
103.60
103.95
103.93
104.25
104.38
104.36
104.32
104.58
104.68
104.92
105.46
105.23
105.58
105.34
105.28
105.70
105.67
105.71
106.19
106.93
107.44
107.85
108.71
109.32
109.49
110.20
110.62
111.22
110.88
111.15
111.29
111.09
111.24
111.45
111.75
111.07
111.17
110.96
110.50
110.48
110.66
110.46
Dataseries Y:
-7	
-6	
-6	
-3	
-2	
-5	
-11	
-11	
-11	
-10	
-14	
-8	
-9	
-5	
-1	
-2	
-5	
-4	
-6	
-2	
-2	
-2	
-2	
2	
1	
-8	
-1	
1	
-1	
2	
2	
1	
-1	
-2	
-2	
-1	
-8	
-4	
-6	
-3	
-3	
-7	
-9	
-11	
-13	
-11	
-9	
-17	
-22	
-25	
-20	
-24	
-24	
-22	
-19	
-18	
-17	




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51742&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51742&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51742&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Bandwidth
x axis0.971346508918404
y axis2.38129506259481
Correlation
correlation used in KDE-0.558284820620082
correlation(x,y)-0.558284820620082

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.971346508918404 \tabularnewline
y axis & 2.38129506259481 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.558284820620082 \tabularnewline
correlation(x,y) & -0.558284820620082 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51742&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.971346508918404[/C][/ROW]
[ROW][C]y axis[/C][C]2.38129506259481[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.558284820620082[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.558284820620082[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51742&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51742&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Bandwidth
x axis0.971346508918404
y axis2.38129506259481
Correlation
correlation used in KDE-0.558284820620082
correlation(x,y)-0.558284820620082



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
if (par3==0) par3 <- dpik(x)
if (par4==0) par4 <- dpik(y)
if (par5==0) par5 <- cor(x,y)
if (par1 > 500) par1 <- 500
if (par2 > 500) par2 <- 500
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par7=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x axis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'y axis',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation used in KDE',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation(x,y)',header=TRUE)
a<-table.element(a,cor(x,y))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')